AI Medical Compendium Journal:
Biomechanics and modeling in mechanobiology

Showing 1 to 10 of 17 articles

Constitutive neural networks for main pulmonary arteries: discovering the undiscovered.

Biomechanics and modeling in mechanobiology
Accurate modeling of cardiovascular tissues is crucial for understanding and predicting their behavior in various physiological and pathological conditions. In this study, we specifically focus on the pulmonary artery in the context of the Ross proce...

Predicting fall parameters from infant skull fractures using machine learning.

Biomechanics and modeling in mechanobiology
When infants are admitted to the hospital with skull fractures, providers must distinguish between cases of accidental and abusive head trauma. Limited information about the incident is available in such cases, and witness statements are not always r...

An explainable machine learning-based probabilistic framework for the design of scaffolds in bone tissue engineering.

Biomechanics and modeling in mechanobiology
Recently, 3D-printed biodegradable scaffolds have shown great potential for bone repair in critical-size fractures. The differentiation of the cells on a scaffold is impacted among other factors by the surface deformation of the scaffold due to mecha...

A physics-informed deep learning framework for modeling of coronary in-stent restenosis.

Biomechanics and modeling in mechanobiology
Machine learning (ML) techniques have shown great potential in cardiovascular surgery, including real-time stenosis recognition, detection of stented coronary anomalies, and prediction of in-stent restenosis (ISR). However, estimating neointima evolu...

Segmenting mechanically heterogeneous domains via unsupervised learning.

Biomechanics and modeling in mechanobiology
From biological organs to soft robotics, highly deformable materials are essential components of natural and engineered systems. These highly deformable materials can have heterogeneous material properties, and can experience heterogeneous deformatio...

Hemodynamic study of blood flow in the aorta during the interventional robot treatment using fluid-structure interaction.

Biomechanics and modeling in mechanobiology
An interventional robot is a means for vascular diagnosis and treatment, and it can perform dredging, releasing drug and operating. Normal hemodynamic indicators are a prerequisite for the application of interventional robots. The current hemodynamic...

A method for real-time mechanical characterisation of microcapsules.

Biomechanics and modeling in mechanobiology
Characterising the mechanical properties of flowing microcapsules is important from both fundamental and applied points of view. In the present study, we develop a novel multilayer perceptron (MLP)-based machine learning (ML) approach, for real-time ...

Machine learning method for extracting elastic modulus of cells.

Biomechanics and modeling in mechanobiology
The Hertz contact mechanics model is commonly used to extract the elastic modulus of the cell, but the basic assumptions of the model are often not met in cell indentation experiments, which can lead to errors in the obtained elastic modulus of cell....

Design and simulation analysis of a bionic ostrich robot.

Biomechanics and modeling in mechanobiology
To look for the reason why the biped animal in nature can run with such high speed and to design a bionic biped prototype which can behave the high speed running and jumping ability, this paper takes the fastest bipedal animal in nature: ostrich as t...

Machine learning for detection of stenoses and aneurysms: application in a physiologically realistic virtual patient database.

Biomechanics and modeling in mechanobiology
This study presents an application of machine learning (ML) methods for detecting the presence of stenoses and aneurysms in the human arterial system. Four major forms of arterial disease-carotid artery stenosis (CAS), subclavian artery stenosis (SAS...